Construction And Prognostic Analysis Of Competitive Endogenous RNA Networks Based On Long Non-coding RNA In Colorectal Cancer

Part One Differential expression of lnc RNA,mi RNA and m RNA and prognostic related genes in colorectal cancer based on TCGA databaseObjective: To study the differential expression of lnc RNA,mi RNA and m RNA in colorectal cancer(CRC),and to further explore the RNA affecting the prognosis of patients with CRC,searching for potential biomarkers of CRC.Methods:1.Download TCGA database transcriptome data and clinicopathological data of patients with colorectal cancer.2.The edge R package in R was used to analyze the differential expression of lnc RNA,mi RNA and m RNA expression respectively between CRC samples and normal samples.3.The differentially expressed m RNA of CRC was used for GO and KEGG pathway enrichment analysis using the package of R language Clusterprofiler.4.Univariate Cox regression analysis and Log-rank test were performed for the differentially expressed DElnc RNA,DEmir RNA and DEm RNA,and Kaplan-Meier survival curve was drawn to screen the prognostic RNA of colorectal cancer.Results:1.Through the differential expression analysis between CRC samples and normal samples,1275 DElnc RNAs,343 DEmir RNAs and 3197 DEm RNAs were screened.2.Clusterprofiler was used to analyze the GO and KEGG pathways enrichment of 3197 dem RNAs,and a total of 1247 GO entries and 57 KEGG signaling pathways were obtained,most of which were related to the occurrence and development of cancer.3.Univariate Cox analysis and Log-rank test confirmed that 21 DElnc RNAs,15 DEmir RNAs and 53 DEm RNAs were significantly associated with the prognosis of CRC.Conclusions:1.Abnormal expressions of lnc RNA,mi RNA and m RNA play important roles in the occurrence and development of CRC.2.Lnc RNA,mi RNA and m RNA can significantly affect the prognosis of patients with CRC,and are also potential molecular markers for the diagnosis and treatment of patients with CRC.Part Two Construction of competitive endogenous RNA network and prognosis signatures for colorectal cancerObjective: Based on the results of differential expression of lnc RNA,mi RNA and m RNA in CRC,we construct a competitive endogenous RNA(ce RNA)network.The prognosis signatures of lnc RNA,mi RNA and m RNA were established by using the network RNAs,and a nomogram was established based on clinicopathological data and the RNA signatures.The prediction efficiency of the histogram model was further evaluated.Methods:1.Bioinformatics method was used to predict the differentially expressed lnc RNAs,mi RNAs and m RNAs interactions in CRC,and the regulatory relationships of lnc RNA-mi RNA and mi RNA-m RNA in the construction of ce RNA network were finally determined after careful matching.The Cytoscape software was used to construct the ce RNA network.2.Cox regression analysis was used to construct prognosis prediction signatures of lnc RNA,mi RNA and m RNA in the ce RNA network,respectively,and the accuracy of the signatures was evaluated.3.The clinicopathological data of CRC in TCGA database and the prognostic prediction signatures of lnc RNA,mi RNA and m RNA were combined to construct the nomogram,and the calibration curve and decision curve were used to evaluate the accuracy of the prediction of the nomogram.Results:1.291 lnc RNAs,137 mi RNAs and 325 m RNAs were included in the ce RNA network,including 1743 lnc RNA-mi RNA pairs and 656 mi RNAm RNA pairs.2.Cox regression analysis was used to construct prognosis prediction signatures containing 15 lnc RNAs,11 mi RNAs and 6 m RNAs,respectively,and the ROC curve showed that all of them had high predictive efficacy.3.The step-by-step multivariate Cox regression analysis was used to construct the nomogram containing the three RNA prediction signatures and clinicopathological data,and the C-index was 0.864.The calibration curve and decision curve indicated that our nomogram had high accuracy and application value.Conclusions:1.We used differentially expressed lnc RNA,mi RNA and m RNA to establish a regulatory network of ce RNA in CRC using bioinformatics method.2.Lnc RNA,mi RNA and m RNA signatures established based on the network have high accuracy in prognosis prediction.3.Combining the clinicopathological data of CRC with the nomogram of lnc RNA,mi RNA and m RNA prediction signatures to further improve the accuracy of prognosis prediction of patients with CRC,which has certain clinical application value.Part Three Long non-coding RNA KCNQ1OT1 as a novel prognostic marker of colorectal cancerObjective: To explore the application value of lnc RNA KCNQ1OT1 as a new prognostic marker for colorectal cancer from the perspective of bioinformatics.Methods:1.The differential expression of KCNQ1OT1 in CRC tissues and normal tissues was calculated using CRC samples from the TCGA and GSE39582 dataset,and the correlation between its expression level and clinical analysis and prognosis was also determined.2.Univariate and multivariate Cox regression analysis was used to determine independent risk factors for prognosis of patients with CRC.3.TCGA database m RNA expression matrix was used to divide CRC into high expression group and low expression group according to the expression level of KCNQ1OT1.GSEA software was used for pathway enrichment analysis.Results:1.The expression level of KCNQ1OT1 in CRC tissues was significantly higher than that in adjacent normal tissues(P < 0.05).2.The expression of KCNQ1OT1 was positively correlated with CRC stage and lymph node metastasis,and the survival time of the group with high KCNQ1OT1 expression was significantly shorter than that of the group with low KCNQ1OT1 expression.3.High expression of KCNQ1OT1 is an independent risk factor for poor prognosis in patients with CRC.4.Upregulated KCNQ1OT1 expression can affect cancer-related pathways,thus promoting the occurrence and development of CRC.Conclusions:1.KCNQ1OT1 is stable and highly expressed in CRC,and is clearly correlated with clinicopathological stage and prognosis of CRC.High expression of KCNQ1OT1 is an independent risk factor for poor prognosis in patients with CRC.2.GSEA enrichment analysis showed that KCNQ1OT1 was associated with the activation of several cancer-related pathways.3.KCNQ1OT1 can be used as a new marker for CRC,but its molecular biological mechanism still needs to be further studied.Part Four Biological function of long non-coding RNA KCNQ1OT1 in colorectal cancerObjective: This study verified the expression of lnc RNA KCNQ1OT1 in CRC tissues,and explored the effects of KCNQ1OT1 knockdown on the proliferation,migration and invasion of CRC cell lines.Methods:1.Real-time PCR was used to detect the expression level of KCNQ1OT1 in 40 pairs of colorectal cancer tissues in our hospital and its adjacent normal tissues.2.After cultured for 48 hours in the KCNQ1OT1-si RNA?si RNA-NC and Blank group,the expression of KCNQ1OT1 in colon cancer cell line SW480 was detected to verify the transfection effect.3.Transwell chamber was used to detect the migration and invasion of colon cancer cells in the KCNQ1OT1-si RNA?si RNA-NC and Blank group.4.The scratch healing ability of colon cancer cells in KCNQ1OT1-si RNA?si RNA-NC and Blank group was detected by scratch test.5.Colony formation experiment to analyze the influence of KCNQ1OT1-mediated SW480 cell colony formation ability.Results:1.The expression level of KCNQ1OT1 in colorectal cancer tissues(median =0.07588)was significantly higher than that in adjacent normal tissues(median =0.01179),the difference was statistically significant(P=0.014).2.Clonal formation experiments showed that KCNQ1OT1 knockdown significantly reduced the colony-forming ability of SW480 cells compared with negative controls.3.Transwell migration chamber experiment results showed that downregulation of KCNQ1OT1 expression significantly reduced the number of SW480 cells in each high-power field,and KCNQ1OT1 knockdown significantly inhibited the migration ability of SW480 cells.4.The scratch experiment results showed that downregulation of KCNQ1OT1 expression could significantly reduce the scratch healing rate.KCNQ1OT1 knockdown significantly inhibited the invasive ability of SW480 cells.Conclusions:1.The expression of KCNQ1OT1 was significantly up-regulated in CRC.2.Downregulation of KCNQ1OT1 in colon cancer cell SW480 can inhibit cell proliferation,colony formation and invasion.3.KCNQ1OT1 plays a carcinogenic role in CRC and can be used as a new prognostic marker for CRC.